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Abstract

This article investigates the asymmetric nature of US stock market return and effect of heteroskedasticity on stock return volatility. Further, this study also analyzes the relationship between stock returns and conditional volatility, and standard residuals. The monthly opening and closing prices of S & P 500 are used for the period from January 1950 to December 2007. The study applies Ljung-Box statistics to examine the autocorrelation in stock returns and GARCH (1, 1) and TAR-GARCH (1, 1) to test the heteroscedasticy, and asymmetric nature of stock returns respectively. The results of the study suggest the presence of non linearity, heteroskedasticity effect and asymmetric nature of stock returns. It also finds no correlation between stock returns and conditional volatility, however, the relationship between stock returns and standardized residuals is found positively significant. These findings bring out the essential elements of the modern investment theory that investors adjust their investment decisions with respect to expected volatility, however, they tend to earn extra risk premium for unexpected volatility. This study provides a robustness test of the conditional volatility and asymmetric impact of good and bad news.

Keywords

Heteroskedasticity GARCH TAR-GARCH S & P 500 conditional volatility unexpected volatility

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References

Aggarwal, A. , Inclan, C. , & Leal, R. 1999). Volatility in emerging markets. Journal of Financial and Quantitative Analysis, 34(1), 33–55.

Akgiray, V. 1989). Conditional Heteroskedasticity in time series of stock returns: Evidence and forecast. Journal of Business, 62(1), 55–80.

Bollerslev, T. 1986). Generalized autoregressive conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.

Bollerslev, T. , Chou, R.Y. , &, Kroner, K.F. 1992). ARCH modeling in finance: A review of the theory and empirical evidence. Journal of Econometrics, 52(1), 5–59.

Brailsford, T.J. , & Faff, R.W. 1996). An evaluation of volatility forecasting techniques. Journal of Banking and Finance, 20(3), 419–438.

Brooks, C. 1998 . Predicting stock index volatility: Can market volume help? Journal of Forecasting, 17(1), 59–80.

Campbell, J.Y. , & Hentschel, L. 1992). No news is good news: An asymmetric model of changing volatility in stock returns. Journal of Financial Economics, 31(3), 281–318.

Chiang, T.C. , & Doong, S.C. 2001). Empirical analysis of stock returns and volatility: Evidence from seven Asian stock markets based on TAR-GARCH Model. Review of Quantitative Finance and Accounting, 17(3), 301–318.

Corhay, A. , & Rad, T. 1994). Statistical properties of daily returns: Evidence from European stock markets. Journal of Business Finance and Accounting, 21(2), 271–282.

10.

Dhankar, Raj S. , & Chakraborty, M. 2007). Non-Linearities and GARCH effects in the emerging stock markets of South Asia. Vikalpa, 32(3), 23–37.

11.

Engle, R. , & Ng, V.K. 1993). Measuring and testing the impact of news on volatility. Journal of Finance, 48(5), 1749–1778.

12.

Engle, R.F. 1982). Autoregressive Conditional Heteroskedasticity with estimates of the variance of United Kingdom Inflation. Econometrica, 50(4), 987–1007.

13.

Faff, W.F. , & Mckenzie, M.D. 2007). The relationship between implied volatility and autocorrelation. International Journal of Managerial Finance, 3(2), 191–196.

14.

French, K.R , Schwert, G.W. , & Stambaugh, R.F. 1987). Expected stock returns and volatility. Journal of Financial Economics, 19(1), 3–29.

15.

Glosten, L.R. , Jagannathan, R. , & Runkle, D.E. 1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance, 48(5), 1779–1801.

16.

Jones, C.P. , & Wilson, J.W. 1989 . Is stock volatility increasing?, Financial Analysts Journal, 45(November–December), 20–37.

17.

Karmakar, M. 2005). Modeling conditional volatility of the Indian stock markets. Vikalpa, 30(3), 21–37.

18.

Kumar, Rakesh . 2007). Economic growth and volatility in Indian stock market: A critical analysis. South Asian Journal of Management, 14(2), 47–59.

19.

Kumar, Rakesh , & Dhankar, Raj S. 2009). Asymmetric volatility and cross correlations in stock returns under risk and uncertainty. Vikalpa, 34(4), 25–36.

20.

Kumar, Rakesh , & Dhankar, Raj S. 2010). Empirical analysis of Conditional Heteroskedasticity in time series of stock returns and asymmetric effect on volatility. Global Business Review, 11(1), 21–33.

21.

Morgan, I.G. 1976). Stock prices and Heteroskedasticity. Journal of Business, 49(4), 496–508.

22.

Nelson, D.B. 1991). Conditional Heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–375.

23.

Pagan, A. , & Schwert, G.W. 1990). Alternative models for common stock volatility. Journal of Econometrics, 45(1), 267–290.

24.

Schwert, G.W. 1990 . Stock market volatility. Financial Analysts Journal, 46(3) (May–June), 23–34.

25.

Sentana, E. , & Wadhwani, S. 1992). Feedback traders and stock returns autocorrelations: Further evidence from a century of daily data. Economic Journal, 102(411), 415–425.

26.

Tsay, R.S. 1998). Testing and modeling multivariate threshold models. Journal of American statistical Association, 93(443), 1188–1202.

27.

Tse, Y.K. 1991). Stock return volatility in the Tokyo Stock Exchange. Japan and World Economy, 3(3), 285–298.

28.

Tse, Y.K. , & Tung, S.H. 1992). Forecasting volatility in the Singapore Stock Market. Asia Pacific Journal of Management, 9(1), 1–13.

29.

Turner, C.M. , Startz, R. , & Nelson, C.R. 1989). A Markov model of heteroskedasticity, risk and learning in the stock market. Journal of Financial Economics, 25(1), 3–22.

30.

Watanabe, T. 2002). Margins requirements, positive feedback trading and stock returns autocorrelations: The case of Japan. Applied Financial Economics, 12(6), 395–403.

Non Linearity and Heteroskedasticity Effect on Stock Returns Volatility

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